Test smarter with generative AI. Pass ISTQB CT-GenAI.
Revision notes that cover the CT-GenAI v1.1 syllabus chapter by chapter — LLM fundamentals, prompt engineering for test tasks, hallucination, privacy and security risks, RAG, agents and LLMOps, and adoption — plus practice that explains every option and timed mocks scored like the real exam.
The CT-GenAI exam at a glance
Official exam details from the ISTQB exam guide — the numbers our mock exams mirror.
Who should take the CT-GenAI?
CT-GenAI is a specialty certification: deep expertise in one domain rather than breadth across the platform.
You specialise in this domain
Specialty exams expect working depth, not survey knowledge. If this domain is your day job, CT-GenAI makes that expertise legible.
You're deepening an existing path
Many candidates add a specialty on top of an associate or professional cert to stand out for roles that name this domain specifically.
What’s on the CT-GenAI exam
Every lesson, question, and mock is weighted to match these official domains.
Introduction to Generative AI for Software Testing
Types of AI, how large language models work (tokens, context windows, multimodal input), foundation vs instruction-tuned vs reasoning models, what LLMs can do for test tasks, and chatbots vs LLM-powered test tools. Official share: 7 of 40 exam questions.
Prompt Engineering for Effective Software Testing
Prompt structure, core prompting techniques (chaining, few-shot, meta prompting), system vs user prompts, applying GenAI to test analysis, design, regression automation and monitoring, and evaluating and refining results. Official share: 11 of 40 exam questions, 16 of 46 points.
Managing Risks of Generative AI in Software Testing
Hallucinations, reasoning errors and biases and how to catch and mitigate them, non-deterministic output, data privacy and security risks, energy use, and the AI regulations, standards and frameworks that apply. Official share: 10 of 40 exam questions.
LLM-Powered Test Infrastructure for Software Testing
Architecture of LLM-powered test tools, Retrieval-Augmented Generation, LLM-powered agents that automate test processes, fine-tuning for test tasks, and LLMOps. Official share: 5 of 40 exam questions.
Deploying and Integrating Generative AI in Test Organizations
Shadow AI, a GenAI strategy for testing, choosing LLMs/SLMs, recurring costs and adoption phases, and the skills, team practices and role changes that adoption brings. Official share: 7 of 40 exam questions.
How you’ll prepare for the CT-GenAI
Three surfaces, one loop: read, drill, rehearse — repeat until your readiness score says book it.
Read the lessons
Work domain by domain through 12 plain-English revision lessons covering every task statement in the CT-GenAI exam guide — key terms, "what's tested" callouts, and takeaways.
Drill every topic
Work through 416 exam-realistic questions in learn mode to study, or quiz mode to test yourself. Every option explains why it’s right or why it’s a trap, with one click back to the lesson.
Rehearse the exam
Sit 3 full-length timed mocks weighted to the official domains and scored on the real CT-GenAI scale — so your mock result predicts your real one.
Exam in a few days? The CT-GenAI cheat sheet puts every lesson’s key takeaways and what’s tested on one page.
Start reading CT-GenAI lessons — no account needed
Open any of these in a new tab and judge the quality yourself. If the lessons don’t earn your time, don’t sign up.
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- Every revision lesson
- 10 practice questions a day
- Cheat sheets & flashcards
- No account needed to start
- All revision lessons
- Full question bank
- All full-length mock exams
- Scaled-score readiness
- Weak-area study plan
- Unlimited practice
CT-GenAI questions, answered
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